Some Impacts of Industry
Clusters in Missouri
Dr. Diane Primont
Professor of Economics &
Associate Director, CEBR
email: dprimont@semo.edu
April 11, 2008
Introduction
 Economists and Economic Developers
often focus on causes of disparities in
economic growth rates
Why?
 Even small differences in growth rates
can lead to ever larger disparities over
time, due to compounding
Two Research Questions
1. Are disparities in economic
performance among counties
increasing or diminishing?

“Convergence”
2. How is this performance
effected by the presence and
extent of industry clusters?

“Industry Clusters”
Two Research Questions
Industry cluster
a group of businesses linked by common
supply chains, labor needs,
technologies, or customers
1. Are Missouri counties
converging?
 Statistical Analysis
 Conditioning
the growth model on:
Rurality
 Industry cluster specialization
 Graphical evidence

Statistical Analysis: Conditioning the
growth model
 Conditional Growth Model
Growth in real per capita income 2000-2005
depends on



Real per capita income in 2000 (lnpcinc2000)
Index of relative rurality (lnirr)
Industry cluster specialization (specialization)
1 if county specializes in one or more industry
clusters; 0 otherwise
Statistical Analysis: Conditioning
the growth model
grpcinc
| Coef. Std. Err. t
P>|t|
------------------------------------------------------------lnpcinc2000 | -.2204 .0342 -6.34 0.000
lnirr
| -.0437 .0150 -2.91 0.004
specialize | .0208 .0096 2.16 0.033
constant
| 2.0510 .3149 6.51 0.000
------------------------------------------------------------R-squared = 0.3005
Adj R-squared = 0.2816
Graphical evidence of convergence
Oregon
Reynolds
Pulaski
St. Louis County
Cape Girardeau
Shelby
Growth by Rurality of County
Reynolds
Carter
Wayne
Scotland
Monroe
Shelby
2. Industry Clusters in Missouri
 Measuring specialization
 Location Quotient
 Specialization in Industries
 Industry cluster bubble charts
 State of Missouri
 Northeast and South Central Missouri
 Southeast Missouri and the Bootheel
Measuring Specialization
 Location Quotient
 Ratio of the proportion of a region’s
employment in an industry to that of
the nation as a whole
 LQ




= (EX/ET)/(NX/NT)
EX is region’s employment industry x
ET is region’s total employment
NX is national employment in industry x
NT is total national employment
Measuring Specialization
 LQ = 1: the region’s activity in the industry
cluster is similar to the nation as a whole.
 LQ < 1: the region’s activity in the industry is
unspecialized.
 The greater LQ exceeds 1, the more
specialized the region is in the industry
cluster.

In this study, a region specializes in an
industry cluster if LQ >= 1.2
0
Printing & Publishing
Mining
MANUFACTURING
SUPERCLUSTER
Transportation &
Logistics
Information Technology
& Telecommunications
Glass & Ceramics
Forest & Wood
Products
Energy (Fossil &
Renewable)
Education &
Knowledge Creation
Defense & Security
Chemicals & Chemical
Based Products
Business & Financial
Services Cluster
Biomedical/Biotechnical
(Life Sciences)
Arts, Entertainment,
Recreation & Vistor
Apparel & Textiles
Agribusiness, Food
Processing &
Advanced Materials
Frequency
Measuring Specialization
Missouri Counties 2005
Frequency Distribution of Specialized Industry Clusters
by industry cluster
30
25
20
15
10
5
Industry Cluster Bubble Chart
Hypothetical Data
LQ in 2005
Mature
2
Stars
1
-10
Transforming
10
0
% Chg. in LQ 2001-2005
Emerging
Industry Cluster Bubble Chart
Missouri's South Central Region
Industry Clusters
LQ2005
Forest &
Wood Products
2.5
Biomedical/
Biotechnical
2
1.5
Education &
Knowledge
Creation
Energy
1
-50
0.5
0
50
0
% chg. in LQ 2001-2005
100
Industry Cluster Bubble Chart
Missouri's Northeast Region
Industry Clusters
LQ in 2005
1.6
Mining
-60
-40
Manufacturing
Supercluster
1.2
-20
0
0.8
20
60
Chemicals
0.4
0
40
Forest &
Wood
Percentage change in LQ 2001-2005
Glass &
Ceramics
Industry Cluster Bubble Chart
Mis s ouri's S outheas t R eg ion
Indus try C lus ters
L Q in 2005
Biomedical/
Biotechnical
-60
-40
Energy
1.6
Forest &
Wood
Product
s -20
Transportation
and Logistics
1.2
0.8
0
20
0.4
0
P ercentage C hange in L Q 2001-2005
40
Defense &
Security
Business &
Financial
60
Industry Cluster Bubble Chart
Missouri Bootheel Region Industry Clusters
2.5
Agribusiness
LQ in 2005
2
Biomedical/Biotechnical
-100
Transportation
and Logistics
1.5
-50
0
50
1
0.5
0
Percentage change in LQ 2001-2005
Manufacturing
Supercluster
100
Conclusions
 Achieving high economic growth is a
challenge for any county or region, but
particularly for rural counties
 Regions with a greater number of “star”
and “emerging” industry clusters tend to
grow faster

May be useful to target these industries for
further development